1768 search results for "regression"

No more ascii-art

January 24, 2013
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No more ascii-art

At least fourfive R packages will turn your regression models into pretty latex tables: texreg, xtable, apsrtable, memisc, and stargazer.  This is very nice if you happen to be a latex document or its final reader, but it’s not so great if you’re making those models to start with. What if you wanted to see

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New book announcement: R and Data Mining – Examples and Case Studies

January 23, 2013
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New book announcement: R and Data Mining – Examples and Case Studies

R and Data Mining: Examples and Case Studies Author: Yanchang Zhao Publisher: Academic Press, Elsevier Publish date: December 2012 ISBN: 978-0-12-396963-7 Length: 256 pages URL: http://www.rdatamining.com/books/rdm This book introduces into using R for data mining with examples and case studies. … Continue reading →

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Reducing Respondent Burden: Item Sampling

January 22, 2013
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Reducing Respondent Burden: Item Sampling

You received confirmation this morning.  Someone made a mistake programming that battery of satisfaction ratings on your online survey.  Instead of each respondent rating all 12 items using a random rotation, only six randomly selected i...

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Reserving based on log-incremental payments in R, part III

January 22, 2013
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Reserving based on log-incremental payments in R, part III

This is the third post about Christofides' paper on Regression models based on log-incremental payments . The first post covered the fundamentals of Christofides' reserving model in sections A - F, the second focused on a more realistic example and model reduction of sections G - K. Today's post will wrap up the paper with sections...

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Quick conversion of a list of lists into a data frame

January 22, 2013
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Quick conversion of a list of lists into a data frame

Data frames are one of R’s distinguishing features. Exposing a list of lists as an array of cases, they make many formal operations such as regression or optimization easy to represent. The R data.frame operation for lists is quite slow, in large part because it exposes a vast amount of functionality. This sample shows one way to write a much...

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Quick conversion of a list of lists into a data frame

January 22, 2013
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Quick conversion of a list of lists into a data frame

Data frames are one of R’s distinguishing features. Exposing a list of lists as an array of cases, they make many formal operations such as regression or optimization easy to represent. The R data.frame operation for lists is quite slow, in large part because it exposes a vast amount of functionality. This sample shows one way to write a much...

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Sums of Random Variables

January 19, 2013
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Sums of Random Variables

I'm currently teaching first-level course in statistical inference for  (mostly) economics students. They've taken a one-semester course in descriptive (economic) statistics, and now we're dealing with sampling distributions, estimation, hypothesis testing, and simple regression analysis.When dealing with the sampling distribution of the sample mean, based on simple random sampling, we derived the result that this distribution has a...

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R package for Bayes factors

January 19, 2013
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Richard Morey writes: You and your blog readers may be interested to know that a we’ve released a major new version of the BayesFactor package to CRAN. The package computes Bayes factors for linear mixed models and regression models. Of course, I’m aware you don’t like point-null model comparisons, but the package does more than The post R...

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Loss reserving has a new, silly name

January 18, 2013
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Loss reserving has a new, silly name

I started using Git some time ago, but mostly for local work files. Today, I finally sync’ed up a repository for loss reserving analysis. It may be found here: https://github.com/PirateGrunt/MRMR MRMR stands for Multivariate Regression Model for Reserves. When pronounced “Mister Mister” it also sounds like a thankfully forgotten American soft pop band from the

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How much can we learn from an empirical result? A Bayesian approach to power analysis and the implications for pre-registration.

January 18, 2013
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How much can we learn from an empirical result? A Bayesian approach to power analysis and the implications for pre-registration.

Just like a lot of political science departments, here at Rice a group of faculty and students meet each week to discuss new research in political methodology. This week, we read a new symposium in Political Analysis about the pre-registration of studies in political science. To briefly summarize, several researchers argued that political scientists should

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